Computer vision systems can be used for automated visual surveillance by setting up a video camera to stream a video feed, associating surveillance rules with positions within the video feed, and determining that objects within the video feed violate the rules. For example, a rule can be to notify a user if an object enters into a selected area within the video feed.
However, such a system has numerous shortcomings. For example, the camera must remain static because if the camera is moved, a previously selected area within the video feed will no longer be associated with the same physical area being monitored. Additionally, rules are associated with a specific camera feed, and cannot be applied to views from other video cameras. Further, rules and areas associated with the rules have to be manually entered, which can require significant manual effort and is prone to human error.
Accordingly, there is a desire for methods, systems, and computer readable media for improved automated visual surveillance in computer vision systems.